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Abstract Thinking


NSF grantees are taking winter weather forecasting beyond El Niño by investigating the relationship between Siberian snow cover in fall months, and Northern Hemisphere climate variability during the winter. The NSF-funded researchers' forecast model has achieved on-target forecasts for major cities in the industrialized countries.

"Weather affects peoples' lives and the global economy on a daily basis," says Anjuli Bamzai, acting director, NSF Division of Atmospheric and Geospace Sciences. "Improving our ability to predict cold weather and heavy snow has obvious benefits. These investigators' real-time forecasts offer the possibility of improving our ability to anticipate such important events."

Forecast Temperature Anomaly

Predicted winter surface temperature anomalies for the United States in Dec-Jan-Feb 2018/19 in degrees Fahrenheit. The model is forecasting below-normal temperatures for the southwestern United States, the Central Rockies, northern California and southern Oregon, with above-normal temperatures for the remainder of the U.S., including the northern and eastern U.S.

The model uses October Siberian snow cover, sea level pressure anomalies, predicted El Niño/Southern Oscillation anomalies and observed September Arctic sea ice concentration anomalies. Siberian snow cover extent is running below normal for the month of October. This is an indication of an increased probability of a strong polar vortex and a predominantly positive Arctic Oscillation during the winter with mild temperatures, especially east of the Mississippi. Forecast date: October 18, 2018.

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A snowstorm buries cars in Baltimore, Maryland.

Germantown, MD: snowstorm. Click for larger image.
A snowstorm hit hard in Germantown, Md. in winter 2003.

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Any opinions, findings, conclusions or recommendations presented in this material are only those of the presenter grantee/researcher, author, or agency employee; and do not necessarily reflect the views of the National Science Foundation.